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Gitta Kutyniok

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PhD or Postdoctoral Position in Spiking Neural Networks, Trustworthy AI and Energy-Efficient Computing Ludwig-Maximilians-Universität München in Germany

Degree Level

PhD, Postdoc

Field of study

Computer Science

Funding

Full-time employment at 100% with remuneration based on qualifications and professional experience up to TV-L E13. The position starts on 2027-02-01 and is limited to 2028-04-30; part-time employment is also possible.

Deadline

Nov 20, 2026

Country flag

Country

Germany

University

Ludwig-Maximilians-Universität München

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Keywords

Computer Science
Deep Learning
Mathematics
Artificial Intelligence
Image Processing
Explainable Ai
Inverse Problem

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About this position

Ludwig-Maximilians-Universität München invites applications for a PhD or postdoctoral position in the Chair for Mathematical Foundations of Artificial Intelligence (MATH4AI), led by Prof. Dr. Gitta Kutyniok at the Mathematical Institute. The position is located in Munich and is connected to an international research team working at the interface of mathematics and artificial intelligence.

The researcher will join the project “Spiking Neural Networks: Theoretical Foundations, Trustworthiness, and Energy-Efficiency”, conducted in cooperation with Prof. Dr. Holger Boche of the Technical University of Munich. Spiking neural networks offer a brain-inspired approach to artificial intelligence and may help address the high energy consumption and limited trustworthiness of current AI systems.

The project develops mathematical foundations for spiking neural networks, with emphasis on reliability, trustworthiness, and energy-efficient AI computing. The work is embedded in the DFG Priority Programme SPP 2298, “Theoretical Foundations of Deep Learning,” providing opportunities to engage with the German interdisciplinary research community in theoretical deep learning.

Responsibilities include conducting research on the project questions, publishing results in leading national and international journals, presenting findings at international conferences, and contributing to activities of the DFG Priority Programme. The MATH4AI environment covers mathematical foundations of AI, representation power, learning, generalization, explainability, image processing, inverse problems, and next-generation AI computing.

The position offers an international and collegial research setting within Munich’s broader AI ecosystem, including initiatives such as AI-HUB@LMU, the Konrad Zuse School of Excellence in Reliable AI, and the Bavaria–Saxony initiative gAIn for next-generation green AI computing.

Funding details

Full-time employment at 100% with remuneration based on qualifications and professional experience up to TV-L E13. The position starts on 2027-02-01 and is limited to 2028-04-30; part-time employment is also possible.

What's required

Applicants need an excellent university degree: a Master's degree for PhD candidates or a doctorate for postdoctoral candidates, in mathematics, computer science, or a related field. A focus on the mathematical foundations of artificial intelligence and/or image processing and inverse problems is desirable. Solid programming skills and business-fluent written and spoken English are required; German is welcome but not required. Applications must include a cover letter, CV, copies of certificates, publication list, and contact details for two references.

How to apply

Submit a single PDF of up to 5 MB containing a cover letter, CV, certificates, publication list, and contact details for two references. Email the application by November 20, 2026, to Prof. Dr. Gitta Kutyniok at [email protected]; questions may be sent to [email protected].

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Professors

Professor

University Name
Country flag

Germany

Research Interests

Computational Neuroscience

Artificial Intelligence

Mathematics

Computer Science

Image Reconstruction

Professor

University Name
Country flag

Germany

Research Interests

Artificial Intelligence

Explainable Ai

Computer Science

Inverse Problem

Mathematics